Techniques associated with 3D (three dimensions) are receiving attention. The techniques associated with 3D have wide applications ranging from military navigation, industrial inspection, to consumer electronics. In recent years, applications and products to which 3D techniques are applied have become available in the market. For instance, 3D televisions are sold by many television manufacturers and 3D movies are shown at various 3D movie theaters. In addition, some television broadcasting companies are broadcasting 3D channels on a trial basis. As stated above, the application of the techniques associated with 3D has increased opportunities for people to experience 3D such as viewing a three-dimensional (3D) video.
Moreover, research on three-dimensional images was started for the techniques associated with 3D in the year 1838. People can perceive a sense of depth due to the parallax between the right eye and the left eye. Accordingly, when a right-eye image and a left-eye image that have an appropriate parallax for the people were generated and the generated right-eye image and the generated left-eye image were respectively sent to the right eye and the left eye of the people, the people would be able to enjoy a realistic three-dimensional (3D) image.
For this reason, various techniques have been developed so as to provide 3D experience suitable for the people. Examples of the developed techniques include 3D image capturing techniques, 3D video capturing techniques, post-processing techniques, and techniques for achieving various functions in a series of 3D processes including, packaging (3D content), 3D content distribution, and 3D display.
Although the 3D televisions have recently made remarkable progress, available 3D contents for home users to enjoy are in short supply. This situation can be mitigated using two solutions.
The first solution is intended to further develop new 3D cameras and market many such 3D cameras. Unfortunately, it takes much time to carry out the first solution. Moreover, the users have to share a burden such as purchasing a new 3D camera.
The second solution is intended to convert 2D video contents into 3D video contents. For instance, examples of this method include a method of converting current 2D video contents into 3D video contents and a method of capturing, with a normal camera or a camcorder, a 2D video and converting 2D video contents into 3D video contents at the same time. The method is more favorable than the development of the new 3D cameras or the like in that the method makes it possible to provide the people with suitable 3D experience without any cost.
PTL 1 discloses a technique of adapting to complexity (low calculation cost) and automatically converting a 2D image (2D video) into a 3D image (3D video). In the technique disclosed by PTL 1, a frame is first classified into a flat image and a non-flat image. Then, the flat image is directly converted into a three-dimensional (3D) display format, and the non-flat image is converted based on a pre-estimated depth map. It is to be noted that the stereo conversion based on the depth map is adaptable to more types of images.
PTL 2 discloses a technique of converting a 2D image signal into a 3D image signal and outputting the converted 3D image signal. In the technique disclosed by PTL 2, the motion of each of frames is first analyzed, and the frames are classified into three types. Specifically, the frames are classified into the following three types: (i) a frame having a horizontal motion and no scene change; (ii) a frame having no horizontal motion and no scene change; and (iii) a frame having no horizontal motion. Next, when frames have the horizontal motion and no scene change, a three-dimensional pair is formed directly using a target frame and the next frame.
NPL 1 discloses a three-dimensional conversion method based on SFM (structure from motion). In the method disclosed by NPL 1, camera parameters such as a position, rotation, and a focal length are estimated using SFM algorithm. Next, a candidate left-eye image and a corresponding right-eye image are selected from an original video sequence based on the estimated camera parameters.